Co-operative Fisheries Inventory Program 2002: Summary Report for the Driftpile and Fawcett River Drainages


Leanne Osokin


The Slave Lake area Co-operative Fisheries Inventory Program (CFIP) is a collaborative
effort of: Alberta Conservation Association (ACA), Alberta Sustainable Resource
Development (SRD), Slave Lake Pulp, and Weyerhaeuser Canada Ltd. (Slave Lake
Division). This was the third season of the CFIP to operate within the industry partner’s
Forest Management Area (FMA). The Driftpile River and the Fawcett River were priority
drainages selected for the 2002 sampling season. Sampling began on May 23 and
concluded on August 27, 2002. In total, 35 sites were completed on the Driftpile River
drainage and 36 sites were completed on the Fawcett River drainage. The Northern East
Slopes (Edson) CFIP team completed 23 sites in the Driftpile drainage in 2001 and are
included as part of the results. Results indicated that 49% of the sites sampled for
fisheries inventory in the Driftpile River drainage contained fish, 51% were barren of fish
and 7 sites were sampled for habitat parameters only. Results indicated that 46.9% of
the sites sampled on the Fawcett River drainage contained fish, 53.1% were barren of
fish, and 4 sites were sampled for habitat only. The permanent sample plots (PSP’s)
established in 2000 on the Marten and Sawridge Creeks were all re-sampled in August
of 2002. The number of Arctic grayling (Thymallus arcticus) increased in the Sawridge
Creek PSP’s while no sport fish were captured in the Marten Creek PSP’s. The
predictive model created by David Board was completed this year, though was not
available for testing in the field season. The model identified important relationships
associated with fish presence and the variables of wetted width and stream order. The
main recommendation from the model was that a more effective sampling protocol would
concentrate sampling efforts on mid-order (2nd, 3rd, and 4th) streams. CFIP industry
partners suggested the model would not be used for future sampling efforts until
government regulators accept these types of predictive sampling initiatives.

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